Tag Archives: PostGreSQL

AWS / Treehouse Software Webinar: Moving Mainframe Data to Snowflake for Enterprise Wide Analytics

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In this episode of the AWS Mainframe Modernization Broadcasting Channel webinar series, you will discover how enterprises are breaking down data silos by migrating mainframe data to Snowflake on AWS. In a real-world case study, see how Treehouse Software handles the complexities of VSAM, Db2, and Adabas data structures to deliver clean, queryable data, ready for modern analytics. Find out how the Treehouse Dataflow Toolkit (TDT) works with virtually any mainframe data replication tool to provide a fully automated approach for rapid and comprehensive data transfer from Kafka streaming pipelines to Snowflake and other Analytics/AI/ML-friendly targets on AWS–AI-ready, with all target resources automatically created.

View the webinar recording here…

Contact Treehouse Software today to request a product demonstration or discuss your data modernization needs…

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Join Treehouse Software for a new episode of the AWS Mainframe Modernization Broadcasting Channel!

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Discover how enterprises are breaking down data silos by migrating mainframe data to Snowflake, enabling unified analytics across legacy and modern systems. In a real-world case study, see how Treehouse Software handles the complexities of VSAM, Db2, and Adabas data structures to deliver clean, queryable data ready for modern analytics.

Meet your presenters…

Sunil Divvela is a Worldwide Specialist Solutions Architect for Mainframe Modernization at AWS. He partners with customers and partners to accelerate their mainframe modernization journeys, leading initiatives from portfolio assessment through post-migration support leveraging Generative AI and Agentic AI. Prior to AWS, Sunil served as a Senior Technology Architect at Infosys, where he led multiple mainframe transformation programs.

Ellie Savova is a Cloud Solutions Architect at Treehouse Software, where she develops and architects AWS-cloud-native SaaS applications focused on enterprise data migrations. She works closely with customers to design secure, scalable cloud-native solutions across hybrid environments, integrating legacy data systems with modern analytics platforms. Ellie also leads customer implementations and innovation initiatives focused on cloud architecture, security, automation, and next-generation data-platform capabilities.

Register now using the QR code above, or HERE!

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Transforming the automotive industry with AI-ready mainframe data delivery to Snowflake and AWS

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by Joseph Brady, Director of Business Development at Treehouse Software

Treehouse Software data delivery for Auto industry

Treehouse Software’s Treehouse Dataflow Toolkit (TDT) is currently in production at a large auto manufacturer as their key component for replicating dealership and vehicle order management data from multiple disparate mainframe databases to Snowflake on AWS.

The TDT solution, along with Treehouse’s decades of mainframe expertise, and our Cloud Engineers’ deep skills with multiple top-level AWS certifications accelerated the customer’s critical data move to Snowflake. Thanks to the Treehouse data delivery architecture, the customer’s data scientists and analysts can now access analytics-ready data through Snowflake. This enables sub-second query performance for rapid, intensive analytical tasks, and data sharing in real time, eliminating the need to move or copy data, thus enabling immediate insights across divisions and subsidiaries. The analytics teams can also make plans to easily add the latest AWS-based Analytics/AI/ML-friendly offerings, such as  Amazon Redshift, Amazon Athena/S3, Amazon SageMaker AI, Amazon Bedrock, as well as any yet-to-be-developed Cloud services!

Since TDT is much more than a mere “connector,” the customer was able to eliminate months of development time and costs by using the tool to quickly and automatically prepared the full infrastructure needed for Snowflake data loading. As shown in the following architectural diagram, TDT is taking the customer’s mainframe data that was pumped into Amazon MSK (Managed Streaming for Kafka) by Rocket Data Replicate and Sync (RDRS) and lands it into Snowflake. TDT not only delivers the customer’s data, but its advanced crawler functions automatically prepare landing tables, views, and staging infrastructure for Snowflake. Additionally, when needed, TDT now stands ready to generate an archiving infrastructure and create Apache Iceberg tables for enhanced data management.

The Treehouse solution is enabling the customer to quickly move away from slow, on-premises, batch-oriented processes to their new scalable, highly available, and secure Cloud-native system. They are also better positioned to innovate for future data needs and strategies on a flexible and easily customizable architecture.

Customer Benefits

  • The customer’s data scientists and analysts can now access analytics-ready data faster and ever before through Snowflake
  • The new architecture easily allows testing and adding other Cloud-based Analytics/AI/ML-friendly targets and services.
  • From a data scientist’s perspective, effective dataflow tooling with TDT has delivered tangible benefits:
    • Fewer reconciliation issues with other divisions
    • Greater confidence in analytical results
    • Faster turnaround on urgent questions from leadership and multiple divisions
  • TDT’s auto scaling and parallelizing Lambda framework allows many parallel selects to all run at once, thus loading large tables with minimal latency.
  • Since TDT is built in alignment with AWS’s and Snowflake’s best practices, proper security and performance is ensured.
  • TDT is delivered via CloudFormation Templates, which automated and accelerated the process of installing and configuring the complete TDT application (including AWS Lambda functions and numerous other AWS resources, all wrapped in a well-architected security framework) in their AWS account. This allowed the customer to be up and running with a fully preconfigured implementation of the new data transfer pipeline in minutes.
  • The customer now has lasting compatibility with emerging Cloud technologies. As AWS and Snowflake introduce new features, TDT readily integrates them, staying ahead of the curve, keeping data pipelines modern and efficient.

In short: better data → better analytical judgment. 

Visit Treehouse Software on the AWS Marketplace for all of our Cloud offerings…

Treehouse Dataflow Toolkit (TDT) and TDT-DIRECT are Copyright © Treehouse Software, Inc. All rights reserved.
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Contact us today to discuss your project! 

Treehouse Software accelerates insurance companies’ data delivery to the latest Analytics/BI/AI/ML-friendly platforms

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by Joseph Brady, Director of Business Development at Treehouse Software and Eleonora Savova, Cloud Solutions Architect at Treehouse Software

Every major insurance policy begins with the same foundation: understanding historical claims data to determine how often claims occur, what they cost, and which factors drive risk.

Data analytics has always been the insurance industry’s lifeblood, with actuarial efforts relying on sophisticated analysis of historical data – an approach that, in many ways, resembles how modern machine learning (ML) techniques are used to quantify and manage risk and uncertainty.

All insurance companies hold decades of valuable data across legacy mainframe and non-mainframe systems. Actuaries, data scientists, and other analysts need data delivered into modern analytics environments in a reliable way. Treehouse Software addresses this challenge in the most straightforward and efficient manner by connecting legacy data to today’s top analytics platforms. Our Treehouse Dataflow Toolkit (TDT) enables rapid bulk load and change data capture (CDC) from multiple data sources into Snowflake and AWS. As part of this process, TDT automatically provides the required target infrastructure, making the data immediately available for Analytics, BI, and AI/ML operations.

TDT serves as a key component within AWS-based actuarial analytics architectures, enabling insurance organizations to move away from slow, on-premises, batch-oriented processes and toward scalable, cloud-native systems. These architectures leverage high-performance computing, data lakes, and serverless technologies to automate data ingestion, modeling, and reporting, reducing processing times from days to minutes.

With TDT handling data delivery, actuaries and data scientists can access analytics-ready data through platforms such as Snowflake, Amazon Redshift, etc. TDT operates in the background, ensuring that the most recent data is consistently available without manual intervention.

TDT Value and Benefits

Beyond delivering your data, TDT is MUCH more than a mere “connector”. It is a fully configurable end-to-end solution designated to manage the complete data delivery lifecycle. TDT’s advanced crawler capabilities automatically prepare landing tables, views, and staging infrastructure required by the target.

TDT is built in alignment with AWS’s and Snowflake’s best practices, ensuring proper security and performance. This consistent adherence to best practices is a key differentiator that sets TDT apart from many other “connectors” on the market.

From an actuary’s perspective, effective dataflow tooling with TDT delivers tangible benefits:

  • Fewer reconciliation issues with Finance
  • Greater confidence in analytical results
  • Faster turnaround on urgent questions from leadership

In short: better data → better actuarial judgment. 

Treehouse provides highly-detailed CloudFormation Templates which automate and accelerate the process of installing and configuring the complete TDT application (including AWS Lambda functions and a number of other AWS resources) in your AWS account(s). The TDT CloudFormation Templates create stacks consisting of all principal framework components, along with related IAM policies and roles which are carefully engineered to comply with “best practices” (such as a “least privileges” approach to permissions).

The TDT CloudFormation Templates also optionally provide for automatic creation of a VPC, its subnets, and all required standard VPC-oriented resources, as well as optional creation of a source database cluster (consisting of either a sample database provided by Treehouse for a quick trial/POC, or your own database and data).

Simply put, TDT is a Cloud-native, turnkey solution that can eliminate months (or even years) of research and development time and costs and allow customers to be up and feeding data to an actuarial analytics architecture in minutes.

Visit Treehouse Software on the AWS Marketplace for all of our Cloud offerings…

Treehouse Dataflow Toolkit (TDT) and TDT-DIRECT are Copyright © Treehouse Software, Inc. All rights reserved.
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Contact us today to schedule a demo! 

Escape the complexity: Treehouse Software’s fully automated, Lambda-based solution accelerates highly scalable data delivery to AWS

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by Joseph Brady, Director of Business Development at Treehouse Software, Inc.

Since 1982, Treehouse Software has been serving enterprises worldwide with industry-leading mainframe software products and outstanding technical support. Today, Treehouse Software brings you Treehouse Dataflow Toolkit (TDT), a serverless (Lambda-based) application that goes beyond basic data transfer. It is a fully automated solution that prepares the full infrastructure needed to automatically prepare the staging infrastructure for the massive data loading to targets, such as Amazon Redshift, Snowflake, Amazon Athena/S3, Amazon S3 Express One Zone Buckets, and Amazon Aurora PostgreSQL. TDT supports data replication between mainframe and non-mainframe sources—without disrupting existing critical work on customers’ legacy systems.

The Treehouse solutions utilizes Rocket Data Replicate and Sync (RDRS) to pull data from the mainframe, where an agent (with a very small footprint) extracts data (either bulk-load or CDC processing). The raw data is then securely passed from the mainframe by RDRS, which transforms and publishes the data to a Kafka topic (in our example above, a topic in an Amazon MSK cluster). The TDT microservices consume the data from MSK/Kafka and land it in S3 buckets, where TDT’s proprietary crawler technology is used to automatically prepare landing tables, views, and additional infrastructure for various analytics friendly targets. Then the mainframe data is loaded into Redshift, Snowflake, S3, or PostgreSQL (all the while adhering to AWS’s and Snowflake’s recommended “best practices” for massive data loading, thus assuring shortest and surest loads). The inherent reliability and scalability of the entire pipeline infrastructure assures near-real-time synchronization between mainframe sources and the target tables, even with very large bulk-loads or transaction-heavy CDC processing.

What about non-mainframe data?

For customers who have non-mainframe data sources, Treehouse offers TDT-DIRECT which pulls data directly from PostgreSQL, SQL Server, Oracle, MySql, and Db2 for bulk-load and CDC into a variety of targets on AWS.

Instantaneous auto scaling…

For massive amounts of data, TDT takes advantage of the auto scaling and parallelizing of the Lambda framework. This allows many parallel selects to all run at once, thus loading large tables with minimal latency. Additionally, all TDT Lambda microservices are fully customizable (they will be YOUR Lambdas) to add extra monitoring capabilities, and any other functionalities for future needs.

TDT’s innovative Lambda-based microservices approach enables faster data flow than any conceivable ODBC-based solution, which is the standard tool used for most “roll your own” approaches, or “we have a connector for that” offerings. TDT offers several key differentiators from standard “connectors” on the market, including:

  • Automatic creation of target resources – TDT automatically prepares landing tables, views, and additional staging infrastructure for the target. Without TDT’s fully automated approach, a customer can spend months designing and creating target resources, such as delta tables, views, schemas, etc.
  • Ease of delivery/implementation – TDT is delivered via CloudFormation templates, which automate and accelerate the process of installing and configuring the complete TDT application (including AWS Lambda functions and numerous other AWS resources, all wrapped in a well-architected security framework) in your AWS account. This allows your site to be up and running with a fully preconfigured implementation of your new data transfer pipeline in minutes.
  • Adherence to best practices – TDTis built in alignment with AWS and Snowflake best practices, ensuring proper security and performance. The fault-tolerant design of the Cloud-native application provides for a robust, future-proof architecture.
  • Adaptability to evolving Cloud ecosystems – In today’s fast-evolving cloud world, TDT’s flexible design ensures lasting compatibility with emerging technologies. As AWS and Snowflake introduce new features, the application readily integrates them, staying ahead of the curve, keeping your data pipelines modern and efficient.

TDT and TDT-DIRECT are designed to deliver: 

  • rapid mainframe and non-mainframe data bulk-loading and CDC to Snowflake and AWS targets
  • access to the latest Analytics, AI, and ML tools and services
  • swift ROI

Contact us today to discuss your needs, or to book a free demo.

Visit Treehouse Software on the AWS Marketplace for all of our Cloud offerings…

Treehouse Dataflow Toolkit (TDT) and TDT-DIRECT are Copyright © Treehouse Software, Inc. All rights reserved.
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Contact us today to schedule a demo! 

Ramp up your AI/ML game with AWS DMS and the TDT-DIRECT Plugin for Snowflake

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by Joseph Brady, Director of Business Development at Treehouse Software, Inc.

Many enterprise customers are using AWS Database Management Service (DMS) to simplify and accelerate migrations across different RDBMSs, such as PostgreSQL, SQL Server, Oracle, etc. and into AWS services like Amazon Redshift, and Amazon Athena/S3.

DMS delivers features for monitoring migration tasks, reviewing AWS CloudWatch metrics, inspecting logs, and validating data, making it a robust and cost effective solution.

Additionally, to ensure the tightest security, DMS implements a comprehensive security framework that safeguards data throughout the migration process using IAM policies, SSL/TLS encryption, and AWS Secrets Manager credential management. Network controls and monitoring tools provide access restriction and real-time visibility. 

High-level look at AWS DMS:

Treehouse Software introduces fully automated connectivity between DMS and Snowflake…

Today’s enthusiasm about AI and ML has become one of the prime motivators for customers wanting to move data to the Cloud, and Snowflake has become the platform of choice for many enterprises looking to mobilize data at near-unlimited scale and performance, while tapping into the most advanced AI/ML tools and services.

For DMS customers looking for the fastest and most straightforward way to connect to Snowflake, Treehouse Software brings you TDT-DIRECT, the ultimate DMS plugin for Snowflake. TDT-DIRECT leverages DMS to provide a turnkey approach that enables rapid bulk load and CDC data transfer directly from RDBMSs to Snowflake–AI-ready, with all target resources automatically created.

TDT-DIRECT is MUCH more than a mere “connector”—it is a serverless (Lambda-based), self-service, end-to-end solution that rapidly prepares the full infrastructure needed for loading data from DMS-supported RDBMSs into Snowflake. TDT-DIRECT’s advanced crawler functions automatically prepare all landing tables, views, and staging infrastructure for Snowflake as seen in this example: 

TDT-DIRECT is built in alignment with AWS’s and Snowflake’s best practices, ensuring proper security and performance. The fault-tolerant design of the AWS-native application provides for a robust, future-proof architecture. This adherence to best practices is a key differentiator of TDT-DIRECT from other “connector” offerings on the market.

Bonus points for fast and easy implementation…

Treehouse provides highly-detailed CloudFormation Templates which automate and accelerate the process of installing and configuring the complete TDT-DIRECT application (including AWS Lambda functions and a number of other AWS resources) in your AWS account(s). The TDT-DIRECT CloudFormation Templates create stacks consisting of all principal framework components, along with related IAM policies and roles which are carefully engineered to comply with “best practices” (such as a “least privileges” approach to permissions).

The TDT-DIRECT CloudFormation Templates also optionally provide for automatic creation of a VPC, its subnets, and all required standard VPC-oriented resources, as well as optional creation of a source database cluster (consisting of either a sample database provided by Treehouse for a quick trial/POC, or your own sample database data).

Simply put, TDT-DIRECT is a Cloud-native, turnkey solution that can eliminate months (or even years) of research and development time and costs, and allow customers to be up and running in minutes.

Visit Treehouse Software on the AWS Marketplace for all of our Cloud offerings…

Treehouse Dataflow Toolkit (TDT) and TDT-DIRECT are Copyright © Treehouse Software, Inc. All rights reserved.
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Contact Treehouse Software for a TDT-DIRECT for Adabas Demo Today!

Contact us today to schedule your session! 

See how Treehouse Software is helping an auto manufacturer replicate mainframe data to Snowflake on AWS without disrupting work on the legacy system

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When Treehouse was approached by a large auto manufacturer to provide a solution to migrate their mainframe data from disparate source databases to Snowflake on AWS, the Treehouse Cloud engineering team was excited to take on the task. It wasn’t long before our experts drew upon their decades of mainframe expertise, along with deep skills and multiple AWS certifications, to come up with a prototype of the Treehouse Dataflow Toolkit (TDT). A quick proof of concept (POC) demonstrated that TDT worked exactly as expected and was the perfect tool for taking mainframe data that was pumped into Amazon MSK (Managed Streaming for Kafka) by Rocket Data Replicate and Sync (RDRS) and landing it into Snowflake on AWS.

TDT accelerated the customer’s move to Snowflake on AWS, because it is much more than a mere “connector” and goes beyond basic data transfer. It’s an automated, end-to-end solution that prepares the full infrastructure needed for Snowflake data loading. Its advanced crawler functions automatically prepare landing tables, views, and staging infrastructure for Snowflake. Additionally, TDT can generate optional archiving infrastructure and create Apache Iceberg tables for enhanced data management.

Treehouse Dataflow Toolkit (TDT) is Copyright © Treehouse Software, Inc. All rights reserved.
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For more information, contact Treehouse Software today!

TREETIP: Auto scaling for massive data loading into Snowflake, Amazon Redshift, etc. with TDT-DIRECT

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by Joseph Brady, Director of Business Development at Treehouse Software, Inc.

Treehouse Dataflow Toolkit Direct (TDT-DIRECT) is a turn-key microservices-based offering that assures auto scalable, highly available, event driven bulk-load and Change Data Capture (CDC) transfers from legacy data sources to data analytics platforms like Snowflake, Amazon Redshift, etc.

This blog focuses on how TDT-DIRECT leverages the auto scaling capabilities of its Lambda microservices. These Lambdas are highly efficient compute services used to process TDT-DIRECT’s data transfer. There is no need to worry about throughput volume with TDT-DIRECT because the Lambdas scale automatically, with new instances spun up as needed  to handle increasing data transfer loads. 

Instantaneous auto scaling…

For massive amounts of data, TDT-DIRECT takes advantage of the auto scaling and parallelizing of the Lambda framework. This allows many parallel selects to all run at once, thus loading large tables with minimal latency.

And that’s not all! Here are TDT-DIRECT’s other key differentiators from standard “connectors” on the market:

  • Automatic creation of target resources – For example, TDT-DIRECT automatically prepares landing tables, views, and additional proprietary staging infrastructure for Snowflake. Without TDT-DIRECT’s fully automated approach, a customer can spend months designing and creating target resources, such as delta tables, views, schemas, etc.
  • Ease of delivery/implementation – TDT-DIRECT is delivered via CloudFormation templates, which automate and accelerate the process of installing and configuring the complete TDT-DIRECT application (including AWS Lambda functions and numerous other AWS resources, all wrapped in a well-architected security framework) in your AWS account. This allows your site to be up and running with a fully preconfigured implementation of your new data transfer pipeline in minutes.
  • Adherence to best practices – TDT-DIRECT is built in alignment with AWS and Snowflake best practices, ensuring proper security and performance. The fault-tolerant design of the Cloud-native application provides for a robust, future-proof architecture.
  • Adaptability to evolving Cloud ecosystems – In today’s fast-evolving cloud world, TDT-DIRECT’s flexible design ensures lasting compatibility with emerging technologies. As AWS and Snowflake introduce new features, the application readily integrates them, staying ahead of the curve, keeping your data pipelines modern and efficient.

Simply put, TDT-DIRECT is a Cloud-native, self-contained, turn-key solution that will eliminate months or years of development time and costs.

Treehouse Dataflow Toolkit (TDT) and TDT-DIRECT are Copyright © 2024 Treehouse Software, Inc. All rights reserved.
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Contact Treehouse Software for a TDT-DIRECT Demo Today!

Contact us today to schedule your session! 

Comprehensive Connectivity and Rapid Data Flow for Enterprise Customers with Treehouse Software and Confluent

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by Joseph Brady, Director of Business Development at Treehouse Software, Inc., Dan Vimont, Director of Innovation at Treehouse Software, Inc., and Ram Dhakne, Staff Solutions Engineer at Confluent

Enterprise customers who are planning to modernize their data on Cloud environments are stating their needs clearly… “We want a way to unify and manage data from our applications, databases, data warehouses, etc., which have long operated in silos.”

These customers also have a crucial need to tap into today’s advanced data analytics platforms, such as Snowflake, Amazon Redshift, and Amazon Athena/S3, where an ever-expanding array of machine learning and artificial intelligence (ML/AI) tools are available to generate vital insights from their enterprise’s data.  Data science teams are eagerly awaiting the arrival of critical data from their enterprise’s data sources to supercharge their predictive analytics and generative AI frameworks.

Data Transfer + Unlimited Scaling and Storage

To address the need for rapid, high-volume data transfer from source DBs to Analytics/ML/AI-friendly platforms, Treehouse Software has recently gone to market with two powerful new offerings: Treehouse Dataflow Toolkit (TDT) for Mainframe Data Sources and TDT-DIRECT for Non-Mainframe Data Sources. These Cloud-native, fully automated, turn-key solutions work hand-in-hand with the premiere data streaming platform, Confluent to empower enterprise customers to rapidly migrate data – both bulk-load and change data capture (CDC) – to Snowflake, Amazon Redshift, Amazon Athena/S3, and Amazon S3 Express One Zone.

The TDT offerings are much more than mere “connectors”, providing an innovative and robust Lambda-based microservices infrastructure that automatically generates all target resources required for data transfer. Without TDT-DIRECT’s fully automated approach, a customer can spend months designing and creating target resources, such as delta tables, views, schemas, etc.

TDT-DIRECT extracts data directly from a source DB and loads it via Confluent into Snowflake’s “delta tables”, which inherently retain the entire history of source data ever since the source-to-target synchronization began (perfect for time-based trend/predictive/prescriptive analytics).

Figure 1: TDT-DIRECT automatically creates all Snowflake target structures (schemas, history tables, current views, user views, stages, and file formats), and Confluent delivers the data (e.g., insert, update, delete transactions) via bulk-load and CDC.

Leveraging AWS CloudFormation for ease of implementation…

For ease of implementation, TDT is delivered via CloudFormation templates, allowing customer sites to be up and running with a fully preconfigured implementation of a new data transfer pipeline in minutes. The TDT CloudFormation Templates create stacks consisting of all principal framework components, along with related IAM policies and roles which are carefully engineered to comply with “best practices” (such as a “least privileges” approach to permissions).

The TDT CloudFormation Templates also optionally provide for automatic creation of a VPC, its subnets, and all required standard VPC-oriented resources, as well as optional creation of a source database cluster (consisting of either a sample database provided by Treehouse for a quick trial/POC, or your own database and data).

The Confluent Advantage…

Treehouse Software’s TDT solutions fully support data transfers from mainframe and non-mainframe data sources to Confluent Cloud, which offers enhanced productivity, improved scalability, minimized downtime, and much more—all while reducing total cost of ownership. Confluent Cloud brings customers a Fully Managed Kafka Service and Complete Pre-Built Ecosystem that includes:

  • Elastic Scaling: Scale up and down quickly to meet fluctuating customer demand, without the ops burden that comes with scaling your data infrastructure.
  • Infinite Storage: Enable powerful use cases by never having to worry about Kafka retention limits again, while only paying for the storage used
  • Built-in Resiliency: Ensure high availability and offload Kafka ops with 99.99% uptime SLA, multi-AZ clusters, and no-touch Kafka patches
  • Serverless stream processing for Apache Flink®: Flink is the de facto industry standard for stream processing. Confluent Cloud for Apache Flink provides a cloud-native, serverless service for Flink that enables simple, scalable, and secure stream processing that integrates seamlessly with Apache Kafka®. Your Kafka topics appear automatically as queryable Flink tables, with schemas and metadata attached by Confluent Cloud.

A Powerful, Combined Solution…

Treehouse Software and Confluent provide a comprehensive framework that allows the target platform to constantly accrue the most current source data, which is ideally suited for data scientists looking to do trend analysis, predictive analytics, ML, and AI work. 

Treehouse Dataflow Toolkit (TDT) and TDT-DIRECT are Copyright ©Treehouse Software, Inc. All rights reserved.
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Contact Treehouse Software for a TDT Demo Today!

Treehouse Software offers SIs and consulting companies free “deep dive” learning sessions to educate your team on the value of bringing these turn-key data transfer solutions your customers.

Contact us today to schedule your session! 

Treehouse Dataflow Toolkit (TDT) Brings Added Value to Systems Integrators and Enterprise Consulting Companies

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TDT_AI_ML

With decades of experience, Treehouse Software has helped systems integrators (SIs) and enterprise consulting companies streamline the migration of mainframe data to modern Cloud and Open Systems platforms—leveraging automation and innovation to accelerate time to value.

Treehouse Software is excited to introduce two powerful new offerings: Treehouse Dataflow Toolkit (TDT) for Mainframe Data Sources and TDT-DIRECT for Non-Mainframe Data Sources. These Cloud-native, fully automated, turn-key solutions empower enterprise customers to rapidly migrate data – both bulk-load and change data capture (CDC) – to advanced cloud and analytics targets such as Amazon Redshift, Snowflake, Amazon Athena/S3, Amazon S3 Express One Zone, and Amazon Aurora PostgreSQL.

TDT for Mainframe Data Sources…

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TDT-DIRECT for Non-Mainframe Data Sources…

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With TDT and TDT-DIRECT, migrations take weeks – not months or years – supported by Treehouse Software’s 40+ years of leadership in data replication.

For SIs and consulting firms, TDT solutions act as critical accelerators – moving enterprise modernization initiatives swiftly into the value capture phase with Cloud and analytics platforms.

Substantial value of solutions that are more than merely “connectors”

  • TDT and TDT-DIRECT are ready to go: Customers can start pumping data into data analytics targets in days, rather than months, or years.
  • TDT and TDT-DIRECT are massively scalable through an efficient, event-driven AWS Lambda-based architecture.
  • TDT’s intelligent crawlers automatically generate JSON-based views and infrastructure – saving developers time and simplifying deployment to analytics environments where SQL-based handling is cumbersome.
  • TDT and TDT-DIRECT are delivered as robust CloudFormation Templates, automating the setup of the full TDT stack (including Lambda functions and other AWS components) within your AWS environment.
  • Treehouse Software provides dedicated technical expertise to ensure fast implementation and continuous support.
  • We say “NO!” to using only generic ODBC connections for data transmission, because:
    • To load large volumes of data, TDT and TDT-DIRECT use native bulk load utilities from target vendors – delivering superior scalability compared to ODBC, which relies on a narrow, transaction-based pipeline.
    • It is important to recognize that Snowflake and Redshift are analytical platforms – NOT OLTP systems—making ODBC-based CDC transfers both inefficient and misaligned with vendor best practices, often causing significant performance bottlenecks.
    • For Snowflake’s bulk-load functionality to operate effectively, proprietary objects beyond basic tables and views are required. TDT’s crawler automatically generates the necessary DDL to provision these components – saving time and preventing errors.

Challenges and impact of building a custom solution

A decision by an enterprise not to use TDT, but instead to build its own Kafka-to-Analytics/ML/AI-friendly targets solution, could result in any, or all, of the following:

  • accumulation of technical debt
  • extensive/unpredictable time to production (6 to 12 months of upfront development on average)
  • ongoing resource planning to maintain home-grown technologies (administrative and development)
  • vendor lock for maintenance of custom-made technologies designed and developed by consultants
  • managing a mix of manual and automated functions (requiring additional ongoing manpower)
  • difficulty in tracking cobbled together components created by multiple staff and consultants
  • limited agility for future customization and innovation (as technologies continue to rapidly evolve)
  • problems adhering to rapidly evolving best practices over time
  • high costs for future growth/scaling
  • potential lack of proper security/ongoing security updates
  • your organization, or your customer has now become an enterprise software development company, along with all of its associated costs!

Simply put, TDT and TDT-DIRECT are comprehensive, turn-key solutions that eliminate the need for months or even years of in-house development and associated costs.

Treehouse Dataflow Toolkit (TDT) and TDT-DIRECT are Copyright © 2024 Treehouse Software, Inc. All rights reserved.
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Contact Treehouse Software for a TDT Demo Today!

Treehouse Software offers SIs and consulting companies free “deep dive” learning sessions to educate your team on the value of bringing these turn-key data transfer solutions your customers.

Contact us today to schedule your session!